Visualization and Interaction with Data-centric applications

We investigate novel visual techniques for interacting with very large or complex data sets. Semantically represented data such as the Linked Open Data Cloud are an important example. We have developed a range of tools and UIs for exploring and searching semantic data such as gFacet or RelFinder. With SemwidgJS, we have developed a JavaScript library that facilitates the integration of Linked Open Data into almost any regular Website. Within the OPDM-project an editor to create and edit semantic product models was realized with a particular focus on non-technical users, thus hiding technical details to achieve a better usability.

Tools for Searching and Exploring Semantic Data

With the steady growth of the Semantic Web, the classical World Wide Web as a network of documents is increasingly transformed into a Web of data. Information is no longer stored as monolithic blocks in web pages, but rather fragmented into many pieces that can be assigned to semantic concepts. We investigate novel forms of interacting with these data sets both in terms of visualization and exploration.


Interfaces for Semantic Data

In order to facilitate the adoption of Semantic Data, intelligent interfaces to create and use such data are vital. Designing and evaluating new approaches to create and use semantic data within regular as well as specialized use-cases are important steps to highlight advantages and benefits of a semantic data model. We strive to develop compelling interfaces which fully exploit all possibilities out of the semantic representation.


Visual Analytics

In this evolving research field, we deal with the development of novel interactive user interfaces for the visualization of unstructured and semi-structured, and possibly very large, sets of data using methods from Visual Analytics. The purpose of these interfaces is to support the user in decision-making and reasoning processes, for example while exploring a large database of products and their properties.



Werner Gaulke


Timo Stegemann


Timm Kleemann


Related publications

Investigating Learnability, User Performance, and Preferences of the Path Query Language SemwidgQL Compared to SPARQL

Stegemann, T., & Ziegler, J. (2017). In C. d’Amato, M. Fernandez, V. Tamma, F. Lecue, P. Cudré-Mauroux, J. Sequeda, … J. Heflin (Eds.), The Semantic Web – ISWC 2017: 16th International Semantic Web Conference, Vienna, Austria, October 21–25, 2017, Proceedings, Part I (pp. 611–627). Cham: Springer International Publishing.

Semantic Models for Adaptive Interactive Systems

Hussein, T., Paulheim, H., Lukosch, S., Ziegler, J., & Calvary, G. (Eds.). (2013). London [u.a.]: Springer.

Interactive Construction of Semantic Widgets for Visualizing Semantic Web Data

Stegemann, T., Ziegler, J., Hussein, T., & Gaulke, W. (2012). In Proceedings of the 4th ACM SIGCHI Symposium on Engineering Interactive Computing Systems. ACM New York, NY, USA.

ChainGraph: A New Approach to Visualize Shared Properties in Resource Collections

Heim, P., & Lohmann, S. (2009). In K. Tochtermann & H. Maurer (Eds.), Proceedings of the 9th International Conference on Knowledge Management and Knowledge Technologies (I-KNOW 09). Graz: J.UCS.

RelFinder: Revealing Relationships in RDF Knowledge Bases

Heim, P., Hellmann, S., Lehmann, J., Lohmann, S., & Stegemann, T. (2009). In T.-S. Chua, Y. Kompatsiaris, B. Mérialdo, W. Haas, G. Thallinger, & W. Bailer (Eds.), Semantic Multimedia - Proceedings of the 4th International Conference on Semantic and Digital Media Technologies. Berlin/Heidelberg: Springer.

Entdecken und Explorieren von Zusammenhängen im Semantic Web

Lohmann, S., Heim, P., Stegemann, T., Tetzlaff, L., & Ziegler, J. (2009). i-Com - Zeitschrift Für Interaktive Und Kooperative Medien, 8(3), 33–39.

gFacet: A Browser for the Web of Data

Heim, P., Ziegler, J., & Lohmann, S. (2008). In S. Auer, S. Dietzold, S. Lohmann, & J. Ziegler (Eds.), Proceedings of the International Workshop on Interacting with Multimedia Content in the Social Semantic Web (IMC-SSW’08). Aachen: CEUR-WS.

Pattern-Based Analysis of SPARQL Queries from the LSQ Dataset

Stegemann, T., & Ziegler, J. (2017). In N. Nikitina, D. Song, A. Fokoue, & P. Haase (Eds.), ISWC 2017 Posters & Demonstrations and Industry Tracks (ISWC-PD-Industry). Aachen.

Rule-enhanced task models for increased expressiveness and compactness

Gaulke, W., & Ziegler, J. (2016). In Proceedings of the 8th ACM SIGCHI Symposium on Engineering Interactive Computing Systems (EICS ’16, pp. 4–15). Brussels, Belgium: ACM.

SemwidgJS: A Semantic Widget Library for the Rapid Development of User Interfaces for Linked Open Data

Stegemann, T., & Ziegler, J. (2014). In E. Plödereder, L. Grunske, E. Schneider, & D. Ull (Eds.), 44. Jahrestagung der Gesellschaft für Informatik, Informatik 2014, Big Data - Komplexität meistern, 22.-26. September 2014 in Stuttgart, Deutschland (Vol. 232, pp. 479–490). GI.


Related projects


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Related developments


A Javascript library to enrich websites with Semantic Data Widgets


X3S is a format for describing semantic stylesheets


Extracts and visualizes relationships between objects in RDF data


Complex semantic querying made easy